Risk Factors of In-hospital Death in COVID-19 Patients: a Meta-analysis
Bibliographic record
Abstract
Background The worldwide COVID-19 pandemic has turned into a global catastrophic public health crisis, and the conclusion about the risk factors of hospital death in COVID-19 patients is not uniform. Objective To explore risk factors of in-hospital death in patients with COVID-19 by a meta-analysis. Methods Case-control studies about risk factors of in-hospital death in COVID-19 patients were searched from databases of the Cochrane Library, ScienceDirect, PubMed, Medline, Wanfang Data, CNKI and CQVIP from inception to October 1, 2021. Literature screening, data extraction and methodological quality assessment were conducted. Meta-analysis was performed using Stata 15.1. Meta-regression was used to explore the potential sources of heterogeneity. Results Eighty studies were included which involving 405 157 cases〔349 923 were survivors (86.37%) , and 55 234 deaths (13.63%) 〕, that were rated as being of high quality by the Newcastle-Ottawa Scale. Meta-analysis showed that being male〔OR=1.49, 95%CI (1.41, 1.57) , P<0.001) , older age〔WMD=10.44, 95%CI (9.79, 11.09) , P<0.001〕, dyspnoea〔OR=2.09, 95%CI (1.80, 2.43) , P<0.001〕, fatigue〔OR=1.49, 95%CI (1.31, 1.69) , P<0.001〕, obesity〔OR=1.46, 95%CI (1.43, 1.50) , P<0.001〕, smoking〔OR=1.18, 95%CI (1.14, 1.23) , P<0.001〕, stroke〔OR=2.26, 95%CI (1.41, 3.62) , P<0.001〕, kidney disease〔OR=3.62, 95%CI (3.26, 4.03) , P<0.001〕, cardiovascular disease〔OR=2.34, 95%CI (2.21, 2.47) , P<0.001〕, hypertension〔OR=2.23, 95%CI (2.10, 2.37) , P<0.001〕, diabetes〔OR=1.84, 95%CI (1.74, 1.94) , P<0.001〕, cancer〔OR=1.86, 95%CI (1.69, 2.05) , P<0.001〕, pulmonary disease〔OR=2.38, 95%CI (2.19, 2.58) , P<0.001〕, liver disease〔OR=1.65, 95%CI (1.36, 2.01) , P<0.001〕, elevated levels of white blood cell count〔WMD=2.03, 95%CI (1.74, 2.32) , P<0.001〕, neutrophil count〔WMD=1.77, 95%CI (1.49, 2.05) , P<0.001〕, total bilirubin〔WMD=3.19, 95%CI (1.96, 4.42) , P<0.001〕, aspartate transaminase〔WMD=13.02, 95%CI (11.70, 14.34) , P<0.001〕, alanine transaminase〔WMD=2.76, 95%CI (1.68, 3.85) , P<0.001〕, lactate dehydrogenase〔WMD=166.91, 95%CI (150.17, 183.64) , P<0.001〕, blood urea nitrogen〔WMD=3.11, 95%CI (2.61, 3.60) , P<0.001〕, serum creatinine〔WMD=22.06, 95%CI (19.41, 24.72) , P<0.001〕, C-reactive protein〔WMD=76.45, 95%CI (71.33, 81.56) , P<0.001〕, interleukin-6〔WMD=28.21, 95%CI (14.98, 41.44) , P<0.001〕, and erythrocyte sedimentation rate〔WMD=8.48, 95%CI (5.79, 11.17) , P<0.001〕 were associated with increased risk of in-hospital death for patients with COVID-19, while myalgia〔OR=0.73, 95%CI (0.62, 0.85) , P<0.001〕, cough〔OR=0.87, 95%CI (0.78, 0.97) , P=0.013〕, vomiting〔OR=0.73, 95%CI (0.54, 0.98) , P=0.030〕, diarrhoea〔OR=0.79, 95%CI (0.69, 0.92) , P=0.001〕, headache〔OR=0.55, 95%CI (0.45, 0.68) , P<0.001〕, asthma〔OR=0.73, 95%CI (0.69, 0.78) , P<0.001〕, low body mass index〔WMD=-0.58, 95%CI (-1.10, -0.06) , P=0.029〕, decreased lymphocyte count〔WMD=-0.36, 95%CI (-0.39, -0.32) , P<0.001〕, decreased platelet count〔WMD=-38.26, 95%CI (-44.37, -32.15) , P<0.001〕, increased D-dimer〔WMD=0.79, 95%CI (0.63, 0.95) , P<0.001〕, longer prothrombin time〔WMD=0.78, 95%CI (0.61, 0.94) , P<0.001〕, lower albumin〔WMD=-1.88, 95%CI (-2.35, -1.40) , P<0.001〕, increased procalcitonin〔WMD=0.27, 95%CI (0.24, 0.31) , P<0.001〕, and increased cardiac troponin〔WMD=0.04, 95%CI (0.03, 0.04) , P<0.001〕were associated with decreased risk of in-hospital death due to COVID-19. According to the meta-regression result, the heterogeneity in gender, renal disease, cardiovascular diseases, asthma, white blood cell count, neutrophil count, platelet count, hemoglobin, and urea nitrogen differed siangificnatly by country (P<0.05) . Conclusion The risk of in-hospital death due to COVID-19 may be increased by 25 factors (including being male, older age, dyspnoea, fatigue, obesity, smoking, stroke, kidney disease, cardiovascular disease, hypertension, diabetes, cancer, pulmonary disease, liver disease, elevated levels of white blood cells, neutrophil count, total bilirubin, aspartate transaminase, alanine transaminase, lactate dehydrogenase, blood urea nitrogen, serum creatinine, C-reactive protein, interleukin-6, and erythrocyte sedimentation rate) , and may be decreased by 13 factors (including myalgia, cough, vomiting, diarrhoea, headache, asthma, low body mass index, decreased lymphocyte count and platelet count, increased D-dimer, longer prothrombin time, lower albumin, increased procalcitonin and cardiac troponin) . The conclusion drawn from this study needs to be further confirmed by high-quality, multicenter, large-sample, real-world studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.065 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".